arabelatso/skills-4-se/cd-pipeline-generator
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Generate GitHub Actions deployment workflows for automated deployment to staging and production environments on cloud platforms (AWS, GCP, Azure). Use when setting up continuous deployment pipelines, creating deployment automation, or configuring multi-environment deployment strategies. Includes templates for environment-specific deployments with approval gates, secrets management, and rollback capabilities.
Install
npx vskill@latest install arabelatso/skills-4-se/cd-pipeline-generatorSKILL.md
CD Pipeline Generator
Overview
Generate production-ready GitHub Actions deployment workflows that automate deployments to staging and production environments with environment protection rules, approval gates, and secrets management.
Workflow
1. Identify Deployment Target
Determine the cloud platform and deployment method:
- AWS: ECS, Elastic Beanstalk, EC2, Lambda
- GCP: Cloud Run, App Engine, Compute Engine, Cloud Functions
- Azure: App Service, Container Instances, Functions
2. Select Template
Use the appropriate template from assets/ based on cloud platform:
deploy-aws.yml- AWS deployments (ECS, Elastic Beanstalk, Lambda)deploy-gcp.yml- GCP deployments (Cloud Run, App Engine)deploy-azure.yml- Azure deployments (App Service, Container Instances)
3. Configure Environments
Set up GitHub environment protection rules for staging and production:
Staging environment:
- Auto-deploy on merge to main/master
- No approval required
- Use staging secrets and variables
Production environment:
- Manual approval required
- Deploy on workflow_dispatch or tag push
- Use production secrets and variables
- Optional: Restrict to specific branches
4. Configure Secrets
Add required secrets to GitHub repository settings (Settings → Secrets and variables → Actions):
AWS:
AWS_ACCESS_KEY_IDAWS_SECRET_ACCESS_KEYAWS_REGION
GCP:
GCP_PROJECT_IDGCP_SERVICE_ACCOUNT_KEY
Azure:
AZURE_CREDENTIALSAZURE_SUBSCRIPTION_ID
5. Customize Deployment Steps
Adapt the template to project-specific deployment needs:
Build artifacts: Add build steps before deployment
Docker images: Build and push container images
Database migrations: Run migrations before deployment
Health checks: Verify deployment success
6. Set Deployment Triggers
Configure when deployments run:
Staging: Auto-deploy on push to main
Production: Manual trigger or tag-based
7. Place Workflow File
Create deployment workflow at .github/workflows/deploy.yml. If multiple deployment workflows are needed (e.g., separate staging and production), use descriptive names:
.github/workflows/deploy-staging.yml.github/workflows/deploy-production.yml
Template Features
All templates include:
- Environment separation: Distinct staging and production deployments
- Approval gates: Production deployments require manual approval
- Secrets management: Secure credential handling via GitHub secrets
- Deployment status: Clear success/failure reporting
- Rollback support: Easy revert to previous versions
- Conditional execution: Deploy only when tests pass
Security Best Practices
- Never commit credentials or API keys to the repository
- Use GitHub environments to scope secrets appropriately
- Enable required reviewers for production deployments
- Use OIDC authentication instead of long-lived credentials when possible
- Implement deployment windows for production (e.g., business hours only)
- Add deployment notifications to Slack/email
Customization Examples
Add deployment notification:
Add rollback capability:
Restrict production deployment time:
Tips
- Start with staging deployments to validate the workflow
- Use environment-specific configuration files (e.g.,
config.staging.json,config.production.json) - Implement blue-green or canary deployments for zero-downtime updates
- Add deployment metrics and monitoring
- Document rollback procedures in the repository
- Test deployment workflows in a separate test environment first
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/cd-pipeline-generator/SKILL.md
Popularity
- Repository stars
- 63
- Repository forks
- 5
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 20 Mar 2026, 7 months ago.
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